ML Scientist - Adversarial Robustness - AI Trainer

About the job

Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey.

Position: LLM Research Scientist (Pre-training & Computer Vision & Adversarial Robustness)
Type: Contract
Compensation: $100–$120/hour
Location: Remote

Role Responsibilities

• Train image classifiers and generative image models from scratch. Fine-tune open-weight language models.
• Optimize models with limited data, compute, and model-size budgets.
• Enhance model robustness to adversarial inputs and conversations.
• Compress models to meet size and latency constraints without losing accuracy.
• Diagnose and resolve training issues effectively.

Qualifications

Must-Have

• 3+ years of machine learning research experience (PhD research counts).
• Strong experience with PyTorch, JAX, TensorFlow, or similar ML frameworks.
• Degree from a top-100 university, experience at a FAANG or comparable AI company, or equivalent research track record through publications or impactful open-source contributions.

Preferred

• Experience in scaling laws and training-efficiency research.
• Knowledge of curriculum learning and data ordering.
• Skills in model evaluation, uncertainty estimation, and model calibration.
• Expertise in data augmentation and synthetic data for robustness.

Application Process (Takes 20–30 mins to complete)

• Upload resume
• AI interview based on your resume
• Submit form

Resources & Support

• For details about the interview process and platform information, please check: https://talent.docs.mercor.com/welcome
• For any help or support, reach out to: support@mercor.com

PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.